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  1. The limits of probability modelling: A serendipitous tale of goldfish, transfinite numbers, and pieces of string. [REVIEW]Ranald R. Macdonald - 2000 - Mind and Society 1 (2):17-38.
    This paper is about the differences between probabilities and beliefs and why reasoning should not always conform to probability laws. Probability is defined in terms of urn models from which probability laws can be derived. This means that probabilities are expressed in rational numbers, they suppose the existence of veridical representations and, when viewed as parts of a probability model, they are determined by a restricted set of variables. Moreover, probabilities are subjective, in that they apply to classes of events (...)
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  • Is the mind Bayesian? The case for agnosticism.Jean Baratgin & Guy Politzer - 2006 - Mind and Society 5 (1):1-38.
    This paper aims to make explicit the methodological conditions that should be satisfied for the Bayesian model to be used as a normative model of human probability judgment. After noticing the lack of a clear definition of Bayesianism in the psychological literature and the lack of justification for using it, a classic definition of subjective Bayesianism is recalled, based on the following three criteria: an epistemic criterion, a static coherence criterion and a dynamic coherence criterion. Then it is shown that (...)
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  • Intuitive And Reflective Responses In Philosophy.Nick Byrd - 2014 - Dissertation, University of Colorado
    Cognitive scientists have revealed systematic errors in human reasoning. There is disagreement about what these errors indicate about human rationality, but one upshot seems clear: human reasoning does not seem to fit traditional views of human rationality. This concern about rationality has made its way through various fields and has recently caught the attention of philosophers. The concern is that if philosophers are prone to systematic errors in reasoning, then the integrity of philosophy would be threatened. In this paper, I (...)
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